nllogis {clinDR}

The negative log likelihood function for a 3- or 4- parameter Emax model on the logit scale for binary dose response.

Description

The negative log likelihood function evaluated with a single input set of parameters for the binary Emax model on the logistic scale. For use with function fitEmax

Usage

nllogis(parms,y,dose,
          prot=rep(1,length(y)),
          count=rep(1,length(y)),
          xbase=NULL)

Arguments

parms

Emax model parameter values. The order of the variables is (log(ED50),Emax,E0) or (log(ED50),lambda,Emax,E0). There must be an E0 for each protocol. Note the transformation of ED50.

y

Binary outcome variable for each patient. Missing values are deleted. Must be coded 0/1.

dose

Dose for each patient

prot

Protocol (group) membership used to create multiple intercepts. The default is a single protocol. The value of prot must be 1,2,3,..

count

Counts for the number of patients with each dose/y value. Default is 1 (ungrouped data).

xbase

Optional matrix of baseline covariates that enter the model linearly. If there is a single covariate, it should be converted to a matrix with one column.

Details

The negative log likelihood for the 3- or 4- Emax model on the logit scale for binary data. Note the ordering of the parameters and their transformations. A 3 vs 4 parameter model is deterimined by the length of parms.

Value

Negative log likelihood value is returned.

Author(s)

Neal Thomas

See Also

nlm, fitEmax

Examples

data('metaData')
exdat<-metaData[metaData$taid==8,]

cy<-round(exdat$sampsize*exdat$rslt)
y<-c(rep(1,length(cy)),rep(0,length(cy)))
cy<-c(cy,exdat$sampsize-cy)
drep<-c(exdat$dose,exdat$dose)
plotD(exdat$rslt,exdat$dose,se=FALSE)
nllogis(parms=c(log(2.5),-3.26,-0.15), y, drep,count=cy)